package com.hj.aiagent.app;

import com.hj.aiagent.advisor.LoggerAdvisor;
import com.hj.aiagent.chatmemory.FileBasedChatMemory;
import com.hj.aiagent.rag.LoveAppRagCustomAdvisorFactory;
import com.hj.aiagent.rag.QueryRewriter;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor;
import org.springframework.ai.chat.client.advisor.QuestionAnswerAdvisor;
import org.springframework.ai.chat.client.advisor.api.Advisor;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.tool.ToolCallback;
import org.springframework.ai.tool.ToolCallbackProvider;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.stereotype.Component;
import reactor.core.publisher.Flux;

import java.util.List;

import static org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor.CHAT_MEMORY_CONVERSATION_ID_KEY;
import static org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor.CHAT_MEMORY_RETRIEVE_SIZE_KEY;

/**
 * @author: hj
 * @description: TODO
 * @date: 2025/7/1 9:41
 */
@Component
@Slf4j
public class LoveApp {

    private final ChatClient client;

    @Resource
    private VectorStore vectorStore;

    @Resource
    private Advisor loveAppRagCloudAdvisor;

    @Resource
    private QueryRewriter queryRewriter;

    @Resource
    private ToolCallback[] toolCallbacks;

    /**
     * ai调用mcp服务
     */
    @Resource
    private ToolCallbackProvider toolCallbackProvider;



    private final String SYSTEM_PROMPT = "扮演深耕恋爱心理领域的专家。开场向用户表明身份，告知用户可倾诉恋爱难题。" +
            "围绕单身、恋爱、已婚三种状态提问：单身状态询问社交圈拓展及追求心仪对象的困扰；" +
            "恋爱状态询问沟通、习惯差异引发的矛盾；已婚状态询问家庭责任与亲属关系处理的问题。" +
            "引导用户详述事情经过、对方反应及自身想法，以便给出专属解决方案。";

    public LoveApp(ChatModel dashscopeChatModel) {
        //基于内存的记忆
        String filePath = System.getProperty("user.dir") + "/chat_memory";
        FileBasedChatMemory chatMemory = new FileBasedChatMemory(filePath);
        this.client = ChatClient.builder(dashscopeChatModel)
                .defaultSystem(SYSTEM_PROMPT)
                .defaultAdvisors(new MessageChatMemoryAdvisor(chatMemory),
                        //自定义日志打印
                        new LoggerAdvisor())
                .build();

    }

    public String doChat(String message, String chatId) {
        ChatResponse chatResponse = client
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                .call()
                .chatResponse();
        String context = chatResponse.getResult().getOutput().getText();
        log.info("context: {}", context);
        return context;
    }

    /**
     * AI 基础对话（支持多轮对话记忆，SSE 流式传输）
     *
     * @param message
     * @param chatId
     * @return
     */
    public Flux<String> doChatByStream(String message, String chatId) {
        return client
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                .stream()
                .content();
    }

    record LoveReport(String title, List<String> suggestions) {
    }

    /**
     * 结构化输出代码
     * @param message 消息
     * @param chatId  聊天 ID
     * @return LoveReport
     */
    public LoveReport doChatWithReport(String message, String chatId) {
        LoveReport loveReport = client.prompt()
                .system(SYSTEM_PROMPT + "每次对话后都要生成恋爱结果，标题为{用户名}的恋爱报告，内容为建议列表")
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                .call()
                .entity(LoveReport.class);
        log.info("LoveReport: {}", loveReport);
        return loveReport;
    }

    /**
     * 基于向量数据库的查询
     * @param message 消息
     * @param chatId  聊天 ID
     * @return LoveReport
     */
    public String doChatWithRag(String message, String chatId) {
        String rewrite = queryRewriter.doQueryRewrite(message);
        ChatResponse chatResponse = client.prompt()
                .system(SYSTEM_PROMPT)
                .user(rewrite)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                .advisors(new LoggerAdvisor())
                .advisors(new QuestionAnswerAdvisor(vectorStore))
                .advisors(LoveAppRagCustomAdvisorFactory.createLoveAppRagCustomAdvisor(vectorStore, "已婚"))
                .call()
                .chatResponse();
        String text = chatResponse.getResult().getOutput().getText();
        log.info("消息：{}", text);
        return text;
    }



    public String doChatWithRagCloud(String message, String chatId) {
        ChatResponse chatResponse = client
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                // 开启日志，便于观察效果
                .advisors(new LoggerAdvisor())
                // 应用增强检索服务（云知识库服务）
                .advisors(loveAppRagCloudAdvisor)
                .call()
                .chatResponse();
        String content = chatResponse.getResult().getOutput().getText();
        log.info("content: {}", content);
        return content;
    }


    /**
     * 使用工具进行聊天
     *
     * @param message 消息
     * @param chatId  聊天 ID
     * @return 字符串
     */
    public String doChatWithTools(String message, String chatId) {
        String rewrite = queryRewriter.doQueryRewrite(message);
        ChatResponse chatResponse = client.prompt()
                .system(SYSTEM_PROMPT)
                .user(rewrite)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                .advisors(new LoggerAdvisor())
//                .advisors(new QuestionAnswerAdvisor(vectorStore))
//                .advisors(LoveAppRagCustomAdvisorFactory.createLoveAppRagCustomAdvisor(vectorStore, "已婚"))
                .tools(toolCallbacks)
                .call()
                .chatResponse();
        String text = chatResponse.getResult().getOutput().getText();
        log.info("消息：{}", text);
        return text;
    }

    /**
     * 调用mcp进行聊天
     *
     * @param message 消息
     * @param chatId  聊天 ID
     * @return 字符串
     */
    public String doChatWithMcp(String message, String chatId) {
        String rewrite = queryRewriter.doQueryRewrite(message);
        ChatResponse chatResponse = client.prompt()
                .system(SYSTEM_PROMPT)
                .user(rewrite)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                .advisors(new LoggerAdvisor())
//                .advisors(new QuestionAnswerAdvisor(vectorStore))
//                .advisors(LoveAppRagCustomAdvisorFactory.createLoveAppRagCustomAdvisor(vectorStore, "已婚"))
                .tools(toolCallbackProvider)
                .call()
                .chatResponse();
        String text = chatResponse.getResult().getOutput().getText();
        log.info("消息：{}", text);
        return text;
    }
}
